Our project "Nindamani: The Weed Removal AgriRobot" won 1st prize🏅 in Autonomous Machines & Robotics category at NVIDIA's AI at the Edge challenge.
Check out the articles on NVIDIA's blog, hackster.io page, and New Scientist's news letter
Nindamani, the AI based mechanically weed removal robot, which autonomously detects and segment the weeds from crop using artificial intelligence. The whole robot modules natively build on ROS2. Nindamani can be used in any early stage of crops for autonomous weeding.
In this following repository, you will find instructions for software installation and control mechanism for Nindamani robot.
- Fully ROS2 compatible
- Battery Operated
- Runtime upto 8-10 hours
- Robotics Arm based weed removal
- Weed detection accuracy upto 85%
- Easy to Operate
| Parameter | Value |
|---|---|
| Robotics OS | ROS2.0 Dashing Diademata |
| System | Ubuntu 18.04 LTS |
| Communication | Wireless , UART(internal motor control) |
| AI Framework | Keras |
| Programming Language | Python3 & C |
| Parameter | Value |
|---|---|
| Degrees of freedom | 3 DOF |
| Error | ±2 mm |
| Payload | 1.5 kg |
| Weight | 35 kg |
| Height | 740 to 860 mm |
| Width | 980 mm |
| Arm Reach | 200x200 sq mm |
| Processor board | Jetson nano Dev Kit |
| Microcontroller | Arduino Mega |
| Servo Motor | 12V DC, 200RPM, 32kgcm H.Torque |
| Stepper Motor | 48V, 6A, Nema 34, 87 kgcm H.Torque |
| Camera | RPi cam ver.2 |
| Wifi card | Intel 8265 |
| USB-TTL cable | PL2303HX chip |
| Battery | 48V 30ah |
In this section we will install all the necessary dependencies in order to be able to launch nindamani robot:
nindamani_agri_robot- integrate all launch node of nindamani robotrpicam_ai_interface- controlling the rpi camera with AI interfaceservo_control- controlling the servo motors with ROS2 interfacestepper_control- controlling the multiple stepper motors with ROS2 interface
- Download latest SDK image: https://developer.nvidia.com/embedded/jetpack
- Completely Format SD card (should not contain any partition). Use Ubuntu default app Disks [Recommeded 64GB SD card]
- Copy ZIP(jetpack image) file to SD card: https://developer.nvidia.com/embedded/learn/get-started-jetson-nano-devkit#write
- Install Keras:
sudo pip3 install keras - Follow this instructions [official from NVIDIA]: https://docs.nvidia.com/deeplearning/frameworks/install-tf-jetson-platform/index.html#prereqs
- Install ROS2 base: https://index.ros.org/doc/ros2/Installation/Dashing/Linux-Install-Debians/
- Make sure that you have colcon in your machine if you are installing from Debian packages.
sudo apt install python3-colcon-common-extensions - For adding additional packages use:
sudo apt install ros-$ROS_DISTRO-<package-name>
- Follow this repo to install Arduino on Jetson nano: https://github.com/JetsonHacksNano/installArduinoIDE.git
- To get Temporary access to USB:
sudo chown <user-name> /dev/tty<usb>andsudo chmod a+rw /dev/tty<usb> - To set Permenantly change USB device permission: http://ask.xmodulo.com/change-usb-device-permission-linux.html
- To control arduino from Command line Source:https://github.com/arduino/arduino-cli
- Clone this repo:
https://github.com/AutoRoboCulture/Arduino-Jetson-nano-interface.git - Place this repo in Arduino Folder
- To setup default wifi connection(Intel 8265 NGW card) while bootup Source: https://desertbot.io/blog/how-to-add-a-dual-wifi-bluetooth-card-to-a-jetson-nano-intel-8265
- follow this steps:
mkdir -p ~/nindamani_ws/src
cd ~/ros2_mara_ws
colcon build
cd src
git clone https://github.com/AutoRoboCulture/nindamani-the-weed-removal-robot.git
- Code:
git clone https://github.com/matterport/Mask_RCNN.git - Copy this cloned repo to
rpicam_ai_interfacepackage:cp Mask_RCNN rpicam_ai_interface/. - Run command:
cd rpicam_ai_interface/Mask_RCNNsudo python3 install setup.py
- Confirm the Library Was Installed:
pip3 show mask-rcnn
- Link for MASK-RCNN preTrained model
- Copy preTrained weights to
rpicam_ai_interfacepackage:mkdir rpicam_ai_interface/preTrained_weights cp mask_rcnn_trained_weed_model.h5 rpicam_ai_interface/preTrained_weights/.
nindamani_ws
├── build
├── install
├── log
└── src
├── nindamani_agri_robot
│ ├── launch
│ └── scripts
├── rpicam_ai_interface
│ ├── scripts
│ ├── preTrained_weights
│ └── Mask-RCNN
├── servo_control
│ ├── config
│ ├── scripts
│ └── srv
└── stepper_control
├── config
├── scripts
├── src
└── srv
- Follow steps:
cd nindamani_ws colcon build
Stepper Motor library implementation on Arduino
- Make sure source setup.bash in bashrc before ROS2 launch command:
echo "source /home/<user-name>/nindamani_ws/install/setup.bash" >> ~/.bashrc - ROS2 Launch command:
ros2 launch nindamani_agri_robot nindamani_agri_robot.launch.py
We have presented the concept that how weeds can be detected from crops using Artifical Intelligence and through delta arm robot weeds are removed autonomously. It's not perfect of course as you can see in the video link but can be improved. Here are some of our ideas which can improvise this robot in future:
- Gripper design enchancement with end tip as arrow shaped.
- Delta arm reach can be improved with high torque stepper motor.
- With RTK-GPS and 4 wheeled drive + 4 wheel steering implementation on robot, it will make whole robot working autonomously.
- Need 3D mapping of land using Lidar, for finding variations in height of crops, weeds and ridge.
@misc{matterport_maskrcnn_2017,
title={Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow},
author={Waleed Abdulla},
year={2017},
publisher={Github},
journal={GitHub repository},
howpublished={\url{https://github.com/matterport/Mask_RCNN}},
}
Kevin Patel
Nihar Chaniyara
Email: autoroboculture@gmail.com
